The requested funding will support a series of scientific meetings to foster a unique, inter- disciplinary and inter-institutional collaboration that has recently been established between public health research scientists at the University of New Mexico Prevention Research Center (PRC) and systems modeling scientists at Sandia National Laboratories (SNL). The focus of our proposed work is on child health with an emphasis on childhood obesity. We are developing a research agenda to integrate community-based public health investigation with systems-based conceptual and computational modeling. We believe that the synthesis of these two approaches will create a more sophisticated framework that will provide insights to strengthen community-level prevention and promote healthier communities. Obesity is a national epidemic with the prevalence of overweight and obesity among children increasing alarmingly over the last several decades.1-7 To date however, obesity has presented a conundrum to prevention science on a number of levels. Part of the challenge has been the complex nature of the problem, both in terms of the factors that influence the development of obesity among individuals in a population, but also in terms of those that influence the success of prevention efforts.8-14 This complexity is difficult to conceptualize, as it includes a variety of factors that exist simultaneously at multiple levels of influence (individual, family, community, state, national), together with the interconnections and relationships formed by the confluence of these factors and their spheres of influence. Increasing acknowledgement that this multiplicity of factors and contexts requires new approaches and perspectives has encouraged support for employing systems-oriented conceptual frameworks in obesity prevention research.15-22 Recent advances in computational modeling make it possible to accommodate increasingly-greater complexity which dovetails with the development of systems-oriented research across disciplines. Considerable interest now exists for applying network science to understanding complex and intersecting socio-ecological factors involved in large-scale public health issues like obesity.19-21, 23 With this in mind, the proposed meetings will allow our workgroup to capitalize on our unique multi-disciplinary partnership and work to integrate systems and network science into the community-based public health approach of the PRC. Our work will culminate in the development of a collaborative PRC/SNL R21 or R01 research grant application. These meetings will provide us with the opportunity to hold regular Team Workshops and periodic intensive Strategic Conceptualization Workshops that will hone our understanding of computational modeling and obesity-prevention frameworks, build the capacity of our workgroup to conduct research that bridges disciplines, and allow us to conceptualize how to integrate community-based approaches with the advances offered by systems-based computational modeling. We will invite prominent experts from relevant fields to share their knowledge and experience with us through workshops, presentations and working discussions. Our goal will be to identify the best modeling approaches and to work with a community to create a prototype Conceptual Model that will be the basis for the R21 or R01 application and for more in-depth future work. We will also form a consortium of researchers interested in this approach. We currently have in mind a network of potential collaborators that could include researchers from other Prevention Research Centers at academic institutions across the country. PUBLIC HEALTH RELEVANCE: The requested funding will support a series of scientific meetings to further develop a unique, inter-disciplinary and inter-institutional collaboration that has recently been established between public health research scientists at the University of New Mexico Prevention Research Center (PRC) and systems modeling scientists at Sandia National Laboratories (SNL). The focus of our proposed work is on child health with an emphasis on childhood obesity. We are developing a research agenda to integrate community-based investigation with systems-based conceptual and computational modeling.